上海电力大学电气工程学部,上海,200090
纸质出版:2026
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李雨洋, 林顺富, 沈运帷, 等. 面向电压三相不平衡抑制的电动汽车聚合商优化调度[J]. 电力系统保护与控制, 2026,54(12).
LI Yuyang, LIN Shunfu, SHEN Yunwei, et al. Optimal EV aggregator scheduling for three-phase voltage unbalance mitigation[J]. Power System Protection and Control, 2026, 54(12).
李雨洋, 林顺富, 沈运帷, 等. 面向电压三相不平衡抑制的电动汽车聚合商优化调度[J]. 电力系统保护与控制, 2026,54(12). DOI: 10.19783/j.cnki.pspc.251385.
LI Yuyang, LIN Shunfu, SHEN Yunwei, et al. Optimal EV aggregator scheduling for three-phase voltage unbalance mitigation[J]. Power System Protection and Control, 2026, 54(12). DOI: 10.19783/j.cnki.pspc.251385.
针对电动汽车通过单相充电桩大规模接入低压配电网引发的三相负荷不均、电压偏移及线路过载等运行风险,以及传统调度方法难以刻画用户偏好的问题,提出一种面向电动汽车聚合商参与的三相不平衡治理与调峰协同优化方法。首先,构建 “用户模糊偏好 - 可量化满意度 - 多目标调度决策” 的闭环框架。利用语言术语集与直觉模糊数对用户接受充电功率调整、相位选择与响应意愿等方面进行刻画,实现语义信息向可计算满意度指标的转化。然后,考虑充电功率调节、换相开关控制及引导用户等多种调节手段,建立用户满意度与聚合商收益的多目标优化调度模型。最后,算例表明所提方法能够有效提升用户参与满意度和聚合商调度灵活性的同时显著降低单相充电集中接入所导致的三相不平衡程度,为电动汽车聚合商调度提供了可行的技术路径。
The large-scale integration of electric vehicles (EVs) into low-voltage distribution networks through single-phase chargers can lead to operational risks
such as three-phase load imbalance
voltage deviation
and line overloading. Meanwhile
traditional scheduling methods often fail to effectively capture user preferences. To address these issues
a coordinated optimization method for three-phase unbalance mitigation and peak shaving involving EV aggregators is proposed. First
a closed-loop framework of "user fuzzy preference-quantifiable satisfaction-multi-objective scheduling decision-making" is constructed. Linguistic term sets and intuitionistic fuzzy numbers are used to characterize users' acceptance of charging power adjustments
phase selection
and response willingness
thereby enabling the transformation of semantic information into computable satisfaction indicators. Considering multiple regulation means
such as charging power regulation
phase-switching control
and user guidance
a multi-objective optimal scheduling model is established to balance user satisfaction and aggregator profits. Finally
case studies show that the proposed method effectively improves user participation satisfaction and enhances the scheduling flexibility of EV aggregators. In addition
it significantly reduces the degree of three-phase unbalance caused by the concentrated integration of single-phase charging loads
providing a feasible technical approach for EV aggregator scheduling.
PUTRUS G A, SUWANAPINGKARL P, JOHNSTON D, et al. Impact of electric vehicles on power distribution networks[C] // 2009 IEEE Vehicle Power and Propulsion Conference, September 7-10, 2009, Dearborn, MI, USA: 827-831.
XU Lei, DOU Chunxia, YUE Dong, et al. Cyber-physical- transportation system based co-design of charging pricing and frequency regulation control for EVs in multi-market[J]. Protection and Control of Modern Power Systems, 2025, 10(6): 1-14.
WANG Jingyuan, BHARATI G R, PAUDYAL S, et al. Coordinated electric vehicle charging with reactive power support to distribution grids[J]. IEEE Transactions on Industrial Informatics, 2019, 15(1): 54-63.
SHI Xiaoying, XU Yinliang, GUO Qinglai, et al. Optimal dispatch based on aggregated operation region of EV considering spatio-temporal distribution[J]. IEEE Transactions on Sustainable Energy, 2022, 13(2): 715-731.
FARAHANI H F. Improving voltage unbalance of low-voltage distribution networks using plug-in electric vehicles[J]. Journal of Cleaner Production, 2017, 148(1): 336-346.
YILMAZ M, KREIN P T. Review of battery charger topologies, charging power levels and infrastructure for plug-in electric and hybrid vehicles[J]. IEEE Transactions on Power Electronics, 2013, 28(5): 2151-2169.
LIAO Chenglin, YANG Bing. Phases-controlled coordinated charging method for electric vehicles[J]. CES Transactions on Electrical Machines and Systems, 2018, 2(1): 3-12.
CHEN Shibo, GUO Zhenwei, YANG Zaiyue, et al. A game theoretic approach to phase balancing by plug-in electric vehicles in the smart grid[J]. IEEE Transactions on Power Systems, 2020, 35(3): 2232-2244.
HUANG Liping, CHEN Dashen, LAI C S, et al. A distributed optimization model for mitigating three-phase power imbalance with electric vehicles and grid battery[J]. Electric Power Systems Research, 2022, 210.
LI Xiangyu, LUO Fengji, ZHANG Cuo, et al. Stochastic EV charging dispatch in unbalanced three-phase networks based on interpretable fuzzy representation of user preferences[J]. IEEE Transactions on Power Systems, 2025, 40(2): 1623-1635.
LI Xiangyu, YIP C, DONG Zhaoyang, et al. Hierarchical control on EV charging stations for PV hosting capacity maximization in unbalanced distribution networks with ancillary service functions[J]. International Journal of Electrical Power Energy Systems, 2024, 160.
AHMAD A, QIN Zian, WIJEKOON T, et al. An overview on medium voltage grid integration of ultra-fast charging stations: current status and future trends[J]. IEEE Open Journal of the Industrial Electronics Society, 2022, 3: 420-447.
ZHANG Mingyang, XU Yinliang, SUN Hongbin. Optimal coordinated operation for a distribution network with virtual power plants considering load shaping[J]. IEEE Transactions on Sustainable Energy, 2023, 14(1): 550-562.
IEEE standard test procedure for polyphase induction motors and generators: IEEE Std 112—2017[S].
WU Yiwei, SHI Jian, LIM G J, et al. Optimal management of transactive distribution electricity markets with co- optimized bidirectional energy and ancillary service exchanges[J]. IEEE Transactions on Smart Grid, 2020, 11(6): 4650-4661.
WANG Zhaoyu, CHEN Bokan, WANG Jianhui, et al. Coordinated energy management of networked microgrids in distribution systems[J]. IEEE Transactions on Smart Grid, 2015, 6(1): 45-53.
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